Maximum flow‐based formulation for the optimal location of electric vehicle charging stations

Pierre-Luc Parent, Margarida Carvalho, Miguel F. Anjos, Ribal Atallah

Article de revue (2024)

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Résumé

With the increasing effects of climate change, the urgency to step away from fossil fuels is greater than ever before. Electric vehicles (EVs) are one way to diminish these effects, but their widespread adoption is often limited by the insufficient availability of charging stations. In this work, our goal is to expand the infrastructure of EV charging stations, in order to provide a better quality of service in terms of user satisfaction (and availability of charging stations). Specifically, our focus is directed towards urban areas. We first propose a model for the assignment of EV charging demand to stations, framing it as a maximum flow problem. This model is the basis for the evaluation of user satisfaction with a given charging infrastructure. Secondly, we incorporate the maximum flow model into a mixed-integer linear program, where decisions on the opening of new stations and on the expansion of their capacity through additional outlets is accounted for. We showcase our methodology for the city of Montreal, demonstrating the scalability of our approach to handle real-world scenarios. We conclude that considering both spacial and temporal variations in charging demand is meaningful when solving realistic instances.

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Organismes subventionnaires:
Hydro-Québec, NSERC / GRSNG Collaborative Research and Developpment, FRQ-IVADO Research Chair in Data Science for Combinatorial Game Theory
Numéro de subvention:
CRDPJ 536757-19
Adresse URL de PolyPublie:
Titre de la revue :
Networks ( vol. 84 , no 2 )
Maison d'édition:
Wiley
OAI:
oai:publications.polymtl.ca:65061
ORCID
Date du dépôt:
09 mai 2025 09:29
Dernière modification:
14 oct. 2026 14:26
Citer en APA 7:
Parent, P.-L., Carvalho, M., Anjos, M. F., & Atallah, R. (2024). Maximum flow‐based formulation for the optimal location of electric vehicle charging stations. Networks, 84(2), 109-131. https://doi.org/10.1002/net.22219

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